CSR: Small: Collaborative Research: Sensorprint: Hardware-Enforced Information Authentication for Mobile Systems

点击翻译按钮获取中文摘要

Today's societies are intricately fused through a vast set of technology-driven networks, mostly mobile-based. Individuals equipped with feature-rich mobile devices are becoming the real-time eyes of world events, providing invaluable insights into remote, hard to access sites and events. However, in critical politically and socially charged settings an acceptable level of trust is difficult, especially since current technologies allow easy forging, manipulation and fabrication of data. The goal of this project is to design and build a mobile data technology with increased authenticity and integrity assurances. Of primary importance is the proof that data have been captured live on the actual mobile device and not fabricated. The new framework will more accurately verify that mobile data and the device sensor streams simultaneously captured are factually related and act as the required witness to the authenticity of reported data - a fundamental role in establishing the credibility of mobile and social media. Applications with important social impact include citizen journalism, smart city management and prototype verification.The project will investigate, develop and evaluate a framework for secure and efficient sensor-based mobile data verification mechanisms. In a first thrust, the team will leverage TrustZone to build a trusted mobile device platform to bootstrap trust into sensor readings captured on the device and provide secure storage and a secure execution environment for sensitive functions. In a second thrust, the team will devise solutions to securely and efficiently capture, authenticate, communicate, archive, search, and access mobile device sensor snapshots ("sensorprints"). Finally, the team will develop mechanisms to verify the consistency between mobile data and simultaneously captured sensor streams. In addition, the developed solutions will be evaluated on newly introduced sensor-centric data plagiarism attacks and mobility based data categories.